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Record W2076342843 · doi:10.1111/1468-2389.00200

Reactions to Managing Counterproductive Behavior through the Implementation of a Drug and Alcohol Testing Program: Americans and Canadians are More Different than You Might Expect

2002· article· en· W2076342843 on OpenAlexaffabout
Gerard Seijts, Daniel P. Skarlicki, Stephen W. Gilliland

Bibliographic record

VenueInternational Journal of Selection and Assessment · 2002
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsPerceptionWork (physics)Test (biology)Substance abuseSocial psychologyAlcohol abusePsychologyPolitical sciencePublic relationsPublic economicsEconomicsPsychiatryEngineering

Abstract

fetched live from OpenAlex

Many organizations have begun to implement drug and alcohol testing programs to screen potential and existing employees for substance abuse in an effort to curb counterproductive behavior at work. Paradoxically, these policies can be seen as unfair and potentially result in counterproductive behavior. The present study investigated whether differences exist between Canada and the USA, two nations that have often been described as ‘indistinguishable’ from one another, with respect to their perceptions of fairness and acceptance of the introduction of a drug and alcohol testing policy in the workplace. Scenarios were used to test the hypotheses. The results showed that Canadians ( N = 163) were less accepting of the policy and perceived the policy as less fair than their American counterparts ( N = 127). In addition, the results showed that the difference between third‐party observers’ and recipients’ acceptance of the policy was less for Canadians than for Americans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.462
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2002
Admission routes2
Has abstractyes

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